code: def SKIP_test_ragged_input_RNN_layer(
      self, layer
  ):  # pylint: disable=invalid-name
      input_data = get_input_dataset(
          tf.ragged.constant([[1, 2, 3, 4, 5], [5, 6]])
      )
  
      layers = [
          ToDense(pad_value=7, mask=True),
          tf.keras.layers.Embedding(8, 16),
          layer(16),
          tf.keras.layers.Dense(3, activation="softmax"),
          tf.keras.layers.Dense(1, activation="sigmoid"),
      ]
      model = get_model_from_layers(
          layers,
          input_shape=(None,),
          input_ragged=True,
          input_dtype=tf.dtypes.int32,
      )
      model.compile(
          optimizer="rmsprop",
          loss="binary_crossentropy",
          metrics=["accuracy"],
      )
  
      output = model.predict(input_data)
      self.assertAllEqual(np.zeros((2, 1)).shape, output.shape)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
  from tensorflow_text.python.keras.layers.todense import ToDense
label_desc: Use image node_id 5 for calling the RaggedTensorsToDenseLayerTest obj's underlying member method code with example usage: obj.SKIP_test_ragged_input_RNN_layer(layer) without return types